python - Pandas logical indexing on a single column of a dataframe to assign values -

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i r programmer , looking similar way in r:

data[data$x > value, y] <- 1

(basically, take rows x column greater value , assign y column @ rows value of 1)

in pandas seem equivalent go like:

data['y'][data['x'] > value] = 1

but gives settingwithcopywarning.

equivalent statements i've tried are:

condition = data['x']>value data.loc(condition,'x')=1

but i'm confused. maybe i'm thinking in r terms , can't wrap head around what's going on in python. equivalent code in python, or workarounds?

your statement incorrect should be:

data.loc[condition, 'x'] = 1

example:

in [3]:  df = pd.dataframe({'a':np.random.randn(10)}) df out[3]:           0 -0.063579 1 -1.039022 2 -0.011687 3  0.036160 4  0.195576 5 -0.921599 6  0.494899 7 -0.125701 8 -1.779029 9  1.216818 in [4]:  condition = df['a'] > 0 df.loc[condition, 'a'] = 20 df out[4]:            0  -0.063579 1  -1.039022 2  -0.011687 3  20.000000 4  20.000000 5  -0.921599 6  20.000000 7  -0.125701 8  -1.779029

as subscripting df should use square brackets [] rather parentheses () function call. see docs


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